This article tries to give an answer to a fundamental question in temporal data mining: "Under what conditions a temporal rule extracted from up-to-date temporal data keeps i...
Most algorithms for computing diagnoses within a modelbased diagnosis framework are deterministic. Such algorithms guarantee soundness and completeness, but are NPhard. To overcom...
Alexander Feldman, Gregory M. Provan, Arjan J. C. ...
Abstract. The paper introduces a reinforcement learning-based methodology for performance improvement of Intelligent Controllers. The translation interfaces of a 3-level Hierarchic...
In this work, probabilistic reachability over a finite horizon is investigated for a class of discrete time stochastic hybrid systems with control inputs. A suitable embedding of ...
Alessandro Abate, Maria Prandini, John Lygeros, Sh...
Monte Carlo methods have been used extensively in the area of stochastic programming. As with other methods that involve a level of uncertainty, theoretical properties are required...